Multi-objective optimization, also referred to as Pareto optimization, is an area of technology dealing with mathematical optimization problems having more than one objective function to be optimized simultaneously. In the areas where optimal decision taking trade-offs into account between multiple conflicting objectives are requested, such as areas of economics, logistics, and engineering, multi-objective optimization techniques are widely used. As multiple objectives are optimized, Pareto optimal solutions may be numerous for a problem.
Cognitive computing attempts to find best solutions in complex situations that are often ambiguous and uncertain, as in human problems, by computing contextual problem based on dynamic and shifting data collected in real time. Cognitive computing utilizes increasingly pervasive digital environment for data collection from people, high-speed processing, and wireless as well as mobile technologies.